Book chapter
The Pragmatics of Destiny in Russian and English (towards a description of fundamental cultural concepts)
This paper deals with the Semantics/Pragmatics distinction in a contrastive ethnolinguistic aspect. I argue for the validity of this distinction based on cross-linguistic data. My claim is that the specificity of the so-called language key words [Wierzbicka 1990:15-17] - linguospecific items particularly representative of a given language speakersђ mentality - is due to pragmatic rather than semantic peculiarities. These pragmatic peculiarities distinguish the key words both from their synonyms within the same language and their counterparts in other languages. The languages under discussion are Russian and English, analyzed within a combined frame of Integral Language Description model [Apresjan 1995:8-238] and Wierzbickaђs ethnolinguistic approach.
In book

«Bankruptcy» Concept Within the Legal Linguistics Coordinates: Russian–English–French Approximations
The article addresses the notion of bankruptcy as perceived by speakers of current Russian, English and French languages both lawyers and participants in professional communication from other trades. Semantic structure of the term is identified based on its lexicographic and regulatory definitions.
In this article we report some new experiments in the area of words clustering for the Russian language. We introduce a new clustering method that distributes words into classes according to their syntactic relations. We used a large untagged corpus (about 7,2 bln of words) to collect a set of such relations. The corpus was processed using a set of finite state automata that extracts syntactically dependent combinations having explicit structure. These automata were used to process only unambiguous text fragments because of combination of these techniques increases the quality of sampled input data. The modification of group average agglomerative clustering was used to separate words between clusters. The sampled set of clusters was tested using one of the semantic dictionaries of the Russian language. The NMI score calculated in this article is equal to 0.457 and F1-score is 0.607.
The brochure presents the curriculum for third- and fourth-year students of Higher School of Economics, studying English as a second language at the Department of World Economy and International Affairs.
The report features the experience of mastering the norms of political correctness in the English language by HSE students by means of creative assignments.